CV
Education
- Northwestern University Evanston, IL - September 2004
- PhD Industrial Engineering and Management Science
- Dissertation: The Use of Hybrid Produce-to-Order/Produce-to-Stock Systems in Multi-Echelon Supply Chains
- Advisors: Dr. Seyed Iravani, Dr. David Simchi-Levi
- The George Washington University Washington, DC
- MA Science, Technology and Public Policy
- University of Illinois at Urbana-Champaign Urbana, IL
- BS General Engineering (Management Science), BA Political Science
Work experience
- Highmark Health
- Lead Data Scientist June 2020-Present Applied machine learning, generative AI, mathematical models for projects supporting healthcare clients. Projects informed efforts for retention, provider relations, and healthcare operations. Clients include Human Resources (People Analytics), General Counsel, provider relations, and AHN (healthcare providers). Represented Highmark Health through professional society activities.
- University of Pittsburgh – Department of Industrial Engineering
- Assistant Professor – January 2009 – June 2023
- RAND Corporation
- Associate Operations Researcher January 2004 – May 2008
Skills
- Programming
- Proficient: Python (NumPy-SciPy), R
- Familiar: Julia, Matlab, Java, Clojure, C/C++, Fortran, Visual Basic for Applications, NetLogo, SQL, Apache Spark
- Tools: Git, Dataiku, Google Cloud/Vertex AI/Gemini/BigQuery, Workday
- Disaster response
- National Planner, Advance Operational Planner, Government Liaison, Disaster Assessment
- Amateur Radio (General), Public Service
Publications
Data Science and Analytics in Healthcare
Luangkesorn, L. (2024). 'Data Science and Analytics in Healthcare.' In L. R. Hardy (Ed.), Health Informatics: An Interprofessional Approach (3rd ed.). Elsevier. ISBN: 978-0-323-71196-8.
Life Cycle Assessment for Long-Term Production Operation
Gaku, R., Luangkesorn, L., & Takakuwa, S. (2021). 'Life Cycle Assessment for Long-Term Production Operation.' DAAAM International Scientific Book 2021, Chapter 11, pp. 131–138.
Machine Learning of Fire Hazard Model Simulations for use in Probabilistic Safety Assessments at Nuclear Power Plants
Worrell, C., Luangkesorn, K. L., Haight, J., & Congedo, T. (2019). 'Machine Learning of Fire Hazard Model Simulations for use in Probabilistic Safety Assessments at Nuclear Power Plants.' Reliability Engineering & System Safety, 183, 128-142.
Analysis of production systems with potential for severe disruptions
'Systems with potential for severe disruptions.' (2016). International Journal of Production Economics, 171, pp. 478–486.
Markov Chain Monte Carlo Methods for Estimating Surgery Duration
Luangkesorn, K. L., & Eren-Doğu, Z. (2015). 'Markov Chain Monte Carlo methods for estimating surgery duration.' Journal of Statistical Computation and Simulation, 86(2).
A Sequential Experimental Design Method to Evaluate a Combination of School Closure and Vaccination Policies to Control an H1N1-Like Pandemic
Luangkesorn, K. L., Ghiasabadi, F., & Chhatwal, J. (2013). 'A Sequential Experimental Design Method to Evaluate a Combination of School Closure and Vaccination Policies to Control an H1N1-Like Pandemic.' Journal of Public Health Management and Practice, 19(Suppl 5), pp. S37–S41.
Practice Summaries: Designing Disease Prevention and Screening Centers in Abu Dhabi
Luangkesorn, K. L., Norman, B. A., Zhuang, Y., Falbo, M., & Sysko, J. (2012). 'Practice Summaries: Designing Disease Prevention and Screening Centers in Abu Dhabi.' Interfaces, 42(4), 406–409.
Modeling Emergency Medical Response to a Mass Casualty Incident Using Agent Based Simulation
Wang, Y., Luangkesorn, L., & Shuman, L. (2012). 'Modeling Emergency Medical Response to a Mass Casualty Incident using Agent Based Simulation.' Socio-Economic Planning Sciences, 46(4), pp. 281–290.
Talks
INFORMS 2026 Panel: AI in the ORMS Workforce: Threat, Tool, or Career Accelerator?
at INFORMS 2026 Annual Conference, San Francisco, CA,
INFORMS 2026 Doctoral Student Colloquium Industry Career Paths Panel
at INFORMS 2026 Annual Conference Doctoral Student Colloquium, San Francisco, CA,
Where Should the Analysts Live: Organizing Analytics Within the Enterprise (University of Alberta)
at Alberta School of Business, University of Alberta,
Development and Deployment of Advance Operational Planning for Disaster Response for the American Red Cross (Columbia)
at Columbia University, Department of Industrial Engineering and Operations Research (IEOR),
INFORMS Analytics 2026 Workshop Using Generative AI in Analytics: Demonstration, Pitfalls, and Practices
Tutorial at INFORMS Webinar / INFORMS Analytics+ 2026,
Fireside Chat: Exploring Generative AI in Healthcare and Emergency Response (CMU)
at Carnegie Mellon University, Heinz College of Information Systems and Public Policy,
INFORMS-Pittsburgh Panel: Mentoring in Analytics
at INFORMS-Pittsburgh, Pittsburgh, PA,
INFORMS 2025 Panel on AI and Optimization for Smarter Healthcare Systems
at INFORMS 2025 Annual Conference, Atlanta, GA,
PyCon USA Does Generative AI Know Statistics?
at PyCon USA 2025, Pittsburgh, PA,
INFORMS Analytics 2025 Where Should Analysts Live: Organizing Analytics Within the Enterprise
at INFORMS-Pittsburgh, Pittsburgh, PA / INFORMS Analytics+, Indianapolis, IN,
INFORMS 2024 Panel on Artificial Intelligence and Generative AI in Analytics Practice
at INFORMS 2024 Annual Conference, Seattle, WA,
POMS 2024 Analyzing Social Vulnerability as a Proxy for Damage in a Natural Disaster
at POMS 2024, Minneapolis, MN,
INFORMS Analytics 2024 Rising Analytics Career Panel
at INFORMS Analytics 2024, Los Angeles, CA,
Information During a Disaster: The Development of Advanced Operational Planning Tools and Model(CMU)
at Carnegie Mellon University, Heinz College of Information Systems and Public Policy,
INFORMS 2023 Panel Successfully Entering the Data Profession
at INFORMS 2023 Annual Conference, Phoenix, AZ,
The Development of Advanced Operational Planning for National Disaster Response at the American Red Cross (University of Pittsburgh)
at University of Pittsburgh, Department of Industrial Engineering,
Tech Talk: Solving the Two Population SIR Model to Project COVID-19 Wave
at ChristianaCare Institute for Research in Equity and Community Health (iREACH) / Delaware-CTR,
INFORMS 2022 Solving the Two Population SIR Model to Provide Early Estimates of Peak and Duration of a COVID-19 Wave
at INFORMS 2022 Annual Meeting, Indianapolis, IN,
INFORMS 2021 Evaluating Specialist Staffing for Telestroke Consult Support for Regional Hospital Emergency Departments
at INFORMS 2021 Annual Meeting, Anaheim, CA / Virtual,
INFORMS 2019 Pro Bono Analytics – Providing Analytics Support to Nonprofit Organizations
at INFORMS 2019 Annual Conference, Seattle, WA,
Bayesian Methods in Python
at Pittsburgh Python Meetup at IBM Pittsburgh,
Natural Language Toolkit and Association Rules
at Pittsburgh Python Meetup at Google Pittsburgh,
Teaching
University of Pittsburgh (Department of Industrial Engineering)
Graduate Courses
- IE 2064: Data Science
- Years Taught: 2014, 2015, 2016, 2017, 2018, 2019, 2020
- IE 2088: Discrete-event Simulation Modeling and Analysis
- Years Taught: 2011, 2013, 2014, 2017, 2018, 2019
- IE 2100: Supply Chain Analysis
- Years Taught: 2015, 2017, 2018
- IE 2073: Design of Experiments
- Year Taught: 2010
Undergraduate & Dual-Level Courses
- IE 1086 / 2086: Decision Models
- Years Taught: 2012, 2013, 2014, 2015, 2019
- IE 0015: Information Systems Engineering
- Years Taught: 2015, 2016, 2017, 2018
- IE 1090: Senior Projects (Capstone Coordinator)
- Years Taught: 2013, 2016, 2017, 2018, 2019, 2020
- Supervised over 100 industry-sponsored BS Industrial Engineering and MHA Health Systems Engineering capstone projects.
Guest Lectures & Executive Education
- Carnegie Mellon University (Tepper School of Business)
- Topic: “Where should analysts live: Organizing analytics in the Enterprise” (Business Analytics: Data-informed Decision Making, Executive Education, Dr. Willem-Jan Van Hoeve, November 2025)
- University of Alberta (Alberta School of Business)
- Topic: “Where should the analysts live: Organizing analytics within the enterprise” (Healthcare Analytics Dr. Saied Samiedaluie, Guest Lecture, May 2026)
- Columbia University (IEOR Department)
- Topic: “Development and deployment of advance operational planning for disaster response for the American Red Cross” (Operations Research for Public Policy Dr. Eric Stratman, Guest Lecture, March 2026)
- University of Pittsburgh
- Topic: “The development of Advance Operational Planning for national disaster response at the American Red Cross.” Guest lecture in IE 1171 Data for the Public Good, Professor Amin Rahimian, University of Pittsburgh, September 17, 2023.
Service
- Institute for Operations Research and Management Science (INFORMS)
- Senior Member
- VP INFORMS-Pittsburgh Chapter January 2025 – Present
- Practice Strategy Committee member, 2025-Present
- AI Integration Committee, 2026
- Certified Analytics Professional Job Task Analysis review committee, 2024
- Institute for Industrial and Systems Engineering Pritsker Dissertation Award Committee (best Health Systems Engineering Dissertation), 2023
- Reviewer for INFORMS Journal of Applied Analytics (2022) Journal of Healthcare Quality (2019), U.S. Department of Energy Office of Science (2019), Applied Mathematical Modeling (2018), U.S. Department of Energy – Office of Nuclear Energy Consolidated Innovative Nuclear Research FOA (2018), Annals of Operations Research (2018), The Python Papers (2015, 2018)
- Reviewer: Manning Press (2015-Present), CRC Press (2015, 2019)
- Consortium for Mathematics and its Applications (COMAP) Interdisciplinary Contest in Modeling (ICM) Triage Judge, 2026.
- Intel International Science and Engineering Fair (ISEF) Judge - Mathematics, Pittsburgh, 2021 (virtual), 2020 (virtual), 2018.
- Simio Student Simulation Competition Judge (2019)